Abstract
Four approximate tests are considered for repeated measurement designs in which observations are multivariate normal with arbitrary covariance matrices. In these tests traditional within-subject mean square ratios are compared with critical values derived fromF distributions with adjusted degrees of freedom. Two of them—the ∈ approximate and the improved general approximate (IGA) tests—behave adequately in terms of Type I error. Generally, the IGA test functions better than the ∈ approximate test, however the latter involves less computations. In regards to power, the IGA test may compete with one multivariate procedure when the assumptions of the latter are tenable.
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Huynh, H.Effect of heterogeneity of covariance on the level of significance of certain proposed tests for the treatment by subject and Type I designs. Unpublished doctoral dissertation. The University of Iowa, 1969.
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The author wishes to thank Garrett K. Mandeville for his careful reading of the final version of the paper.
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Huynh, H. Some approximate tests for repeated measurement designs. Psychometrika 43, 161–175 (1978). https://doi.org/10.1007/BF02293860
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DOI: https://doi.org/10.1007/BF02293860